Tensor-based multiscale method for diffusion problems in quasi-periodic heterogeneous media

TL;DR

This paper develops a tensor-based multiscale numerical method for efficiently solving diffusion problems in quasi-periodic heterogeneous media, reducing computational complexity through low-rank tensor approximations.

Contribution

It introduces a novel two-scale tensor framework and a discontinuous Galerkin formulation for multiscale diffusion equations in quasi-periodic media.

Findings

Efficient low-rank tensor approximations of solutions.

Reduced computational complexity for multiscale simulations.

Framework applicable to complex quasi-periodic media.

Abstract

This paper proposes to address the issue of complexity reduction for the numerical simulation of multiscale media in a quasi-periodic setting. We consider a stationary elliptic diffusion equation defined on a domain $D$ such that $\overline{D}$ is the union of cells $\{\overline{D_i}\}_{i\in I}$ and we introduce a two-scale representation by identifying any function $v(x)$ defined on $D$ with a bi-variate function $v(i,y)$, where $i \in I$ relates to the index of the cell containing the point $x$ and $y \in Y$ relates to a local coordinate in a reference cell $Y$. We introduce a weak formulation of the problem in a broken Sobolev space $V(D)$ using a discontinuous Galerkin framework. The problem is then interpreted as a tensor-structured equation by identifying $V(D)$ with a tensor product space $\mathbb{R}^I \otimes V(Y)$ of functions defined over the product set $I\times Y$. Tensor numerical methods are then used in order to exploit approximability properties of quasi-periodic solutions by low-rank tensors.